Variant interpreter

Manufactured by Illumina

Sourced in United States

The Variant Interpreter is a software tool designed to analyze and interpret genetic variants identified through DNA sequencing. It provides a comprehensive platform for annotating, filtering, and prioritizing variants of interest. The core function of the Variant Interpreter is to assist researchers and clinicians in the interpretation of genetic data, facilitating the identification of clinically relevant variants.

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Lab products found in correlation

Nextseq 550dx sequencer, by Illumina (1 mentions) Dna amplicon, by Illumina (1 mentions) Annovar, by Illumina (1 mentions) Quibit dsdna br assay kits, by Thermo Fisher Scientific (1 mentions) Nanodrop, by Thermo Fisher Scientific (1 mentions) Qiaamp dna mini kit, by Qiagen (1 mentions) Ion reporter, by Thermo Fisher Scientific (1 mentions) Sureselect xt, by Agilent Technologies (1 mentions) Miseq sequencer, by Illumina (1 mentions) Bigdye terminator v3.1 cycle sequencing kit, by Thermo Fisher Scientific (1 mentions) Basespace, by Illumina (1 mentions) Nextseq 500, by Illumina (1 mentions) Phix control library, by Illumina (1 mentions)

9 protocols using variant interpreter

Germline Variant Analysis for Osteogenesis Imperfecta

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Data (VCF files) were obtained using the DNA Amplicon (Illumina) module and analyzed by Evai (Engenome, https://evai.engenome.com/#app/analysis/11919), Variant Interpreter (Illumina, https://variantinterpreter.informatics.illumina.com/registry/cases), and Varsome Clinical (https://varsome.com). Briefly, the DNA Amplicon module was used to align the reads to the reference genome (hg19) and then to run to search for germline variants in the targeted regions. Variant classification is based on the current ACMG standards and guidelines. All variants were reviewed using VARSOME (https://varsome.com), the Osteogenesis Imperfecta Variant Database (oi.gene.le.ac.uk), dbSNP (http://www.ncbi.nlm.nih.gov/projects/SNP/), and Clinvar (https://www.ncbi.nlm.nih.gov/clinvar/).
The software VarSeq 2.3.0 (Golden Helix) was also used to confirm PVs detected in this study.

Paduano F., Fischetto R., Moretti B., De Vito D, & Tatullo M. (2023). Expanding the genetic and clinical spectrum of osteogenesis imperfecta: identification of novel rare pathogenic variants in type I collagen-encoding genes. Frontiers in Endocrinology, 14, 1254695.

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Exome Sequencing and Somatic Variant Analysis

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Raw data in fastq format were first analyzed for quality using FastQC v0.11.9 software (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (Accessed 26 March 2021). Exome analysis was performed using the SeqMule pipeline [37 (link)] that enables the performance of all steps required for variant calling (alignment, re-alignment, quality score recalibration, and variant calling). To obtain somatic mutations, Mutect2 (https://gatk.broadinstitute.org/hc/en-us/articles/360037593851-Mutect2) (Accessed 8 April 2021) was used to pair the tumor tissue DNA with its corresponding control blood germinal DNA. Somatic variant annotation was performed using Illumina Variant Interpreter (https://variantinterpreter.informatics.illumina.com/home) (Accessed 31 March 2021). Summary tables and graphs were created using the R package, Maftools (https://bioconductor.org/packages/release/bioc/html/maftools.html) (Accessed 22 April 2021).
The Integrative Onco Genomics (IntOGEn) framework (https://intogen.org) (Accessed 8 April 2021) was used to identify the presence of driver genes in the mutated genes. Moreover, we questioned the VarSome (https://varsome.com/) (Accessed 15 April 2021) engine, which consists of a set of tools and platforms to analyze human genetic variations.

Lessi F., Morelli M., Franceschi S., Aretini P., Menicagli M., Marranci A., Pasqualetti F., Gambacciani C., Pieri F., Grimod G., Zucchi V., Cupini S., Di Stefano A.L., Santonocito O.S, & Mazzanti C.M. (2023). Innovative Approach to Isolate and Characterize Glioblastoma Circulating Tumor Cells and Correlation with Tumor Mutational Status. International Journal of Molecular Sciences, 24(12), 10147.

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Whole Exome Sequencing for Retinal Disorder Diagnosis

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Whole Exome Sequencing (WES) was performed in case I:2 on genomic DNA extracted from peripheral blood. Target DNA regions were enriched by Nextera DNA Exome probes (Illumina, San Diego, CA, USA) and then sequenced on NextSeq550Dx sequencer (Illumina). Sequencing reads were aligned to the human reference genome (UCSC hg19) by BWA (v0.7.7-isis-1.0.2) (Illumina). Variant calling was performed by GATK Variant Caller (v1.6-23-gf0210b3). The DNA variants were annotated by Variant Interpreter (v.2.13.0.20) (Illumina). Variants’ mapping in genes associated to retinal disorders was prioritized and then filtered by MAF < 0.01 (GnomAD v2.1). Filtered variants were classified according to ACMG-AMP criteria [9 (link)]. The filtered variant was tested by Sanger sequencing both in case I:2 as well as in cases II:1, II:2, III:1 and III:2, with the following primers’ pair (annealing temperature: 56 °C, extension time: 30″):
CHM Ex10 FW: 5′-AGCCCTCAAAATAGCAACAAG-3′
CHM Ex10 Rv: 5′-CCCTAAAACCAGACCCTGTA-3′
To analyze the functional effect of the CHM splicing variant, mRNA from peripheral blood of case II:2 was retro-transcribed into cDNA and then sequenced by the Sanger technique with the following primers’ pair, spanning from CHM exon 8 to 13:
CHM Ex8-13 FW: 5′-CAATGACATCAGAGACAGCCA-3′
CHM Ex8-13Rv: 5′-TGTGCAAGTCAAATGAACCAA-3′

Di Giosaffatte N., Valiante M., Tricarico S., Parise G., De Negri A.M., Ricciotti G., Florean L., Paiardini A., Bottillo I, & Grammatico P. (2022). A Novel Hypothesis on Choroideremia-Manifesting Female Carriers: Could CHM In-Frame Variants Exert a Dominant Negative Effect? A Case Report. Genes, 13(7), 1268.

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Genetic Profiling of UC-MSCs for Manufacturing

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Once the culture of selected UC-MSCs at P2 reached 80% confluence, they were harvested for further expansion, and two million UC-MSCs were collected for DNA extraction using a QIAamp DNA Mini Kit (Qiagen). The DNA concentration and quality were measured with a Nanodrop and Quibit dsDNA BR Assay kits (Invitrogen, US). The TruSight One Expanded Sequencing Panel, which covers the coding regions of 6794 genes and 16.6 Mb of genomic content, was used for DNA library preparation, and then the size and quality of the DNA library were calculated by Quibit and Tape Station (Agilent, US). The NextSeq 550 High Output Kit (v2.5) was used for DNA sequencing. BWA-MEM and DRAGEN-GATK software were used for alignment and variant calling. Variants were classified according to ACMG and AMP guidelines by TAPE, ANNOVAR, and Variant Interpreter (Illumina, US). Three cell lines that met all screening criteria were randomly selected for the manufacturing process.

Hoang D.M., Nguyen Q.T., Phan T.T., Ngo A.T., Pham P.T., Bach T.Q., Le P.T., Bui H.T, & Thanh L.N. (2023). Advanced cell-based products generated via automated and manual manufacturing platforms under the quality by design principle: Are they equivalent or different?. Heliyon, 9(5), e15946.

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Targeted Sequencing of Genetic Variants

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Genomic DNA was isolated from all patients (n = 1043) who had available blood samples using the Gentra Clotspin and Puregene DNA purification kits (Qiagen, Valencia, CA, USA) and quantitated by fluorometry. Libraries were created from 50 ng of DNA using the TruSight Rapid Capture kit and TruSight cancer panel and sequenced on a MiSeq (Illumina, Inc., San Diego, CA, USA) according to manufacturer’s protocols. Data were analyzed using Variant Interpreter (Illumina, Inc., San Diego, CA, USA) and filtered for missense or frameshift mutations, stop gains or losses, initiator codons, in-frame insertions or deletions, and splice site alterations with a minor allele frequency of ≥0.25. The predicted effect of variants was evaluated using the ClinVar database (http://www.clinvar.com/) and classified as pathogenic, likely pathogenic, VUS, likely benign, or benign. Only variants from multiple submitters with no conflicts or that were reviewed by an expert panel were considered pathogenic or likely pathogenic.

Rummel S.K., Lovejoy L.A., Turner C.E., Shriver C.D, & Ellsworth R.E. (2020). Should Genetic Testing for Cancer Predisposition Be Standard-of-Care for Women with Invasive Breast Cancer? The Murtha Cancer Center Experience. Cancers, 12(1), 234.

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Variant Identification in Cancer Genomics

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The sequences were aligned with the reference genome NCBI Build 37 (UCSC hg19). Variants were then identified by the Variant Caller algorithm and the annotation of variants was performed with the Ion Reporter (Life Technologies, Carlsbad, CA, USA) and Variant Interpreter (Illumina, San Diego, CA, USA). We mapped reads to the hg19 reference genome using the Integrated Genome Viewer (IGV v2.3; Broad Institute, Cambridge, MA, USA). The Catalogue of Somatic Mutations in Cancer (COSMIC), the National Center for Biotechnology ClinVar and cBioPortal for Cancer Genomics database were checked to identify pathogenetic changes. In addition, the variants were analysed with two mutational functional prediction programs (sift and polyphen-2).

Boiza-Sánchez M., Manso R., Balagué O., Chamizo C., Askari E., Salgado R.N., Blas-López C., Aguirregoicoa-García E., Menárguez J., Santonja C., Adrados M., Limeres-González M.Á., Piris M.Á, & Rodríguez-Pinilla S.M. (2020). Lymphoplasmacytic lymphoma associated with diffuse large B-cell lymphoma: Progression or divergent evolution?. PLoS ONE, 15(11), e0241634.

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Genetic Analysis of Vitamin D Deficiency

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Genomic DNA was extracted from peripheral blood leukocytes by standard procedures. A DNA sample of the proband was analyzed by next-generation sequencing (NGS) using a customized SureSelectXT (Agilent) panel targeting selected vitamin D-associated genes, according to the protocol supplied. Sequencing was carried out in a MiSeq sequencer (Illumina) using the pair end format. The sequencing results were analyzed using the application Variant Interpreter (Illumina); sequence revision against the human genome was carried out using the Integrative Genomes Viewer. Direct Sanger sequencing (BigDye Terminator v3.1 Cycle sequencing Kit, Life Technologies, Italy) was performed to confirm genetic variants individuated by NGS and to screen the other members of the family. DNA from the nonblood relatives was analyzed by NGS, using the same customized SureSelectXT (Agilent) panel targeting selected vitamin D associated genes.

Brancatella A., Cappellani D., Kaufmann M., Borsari S., Piaggi P., Baldinotti F., Caligo M.A., Jones G., Marcocci C, & Cetani F. (2021). Do the Heterozygous Carriers of a CYP24A1 Mutation Display a Different Biochemical Phenotype Than Wild Types?. The Journal of clinical endocrinology and metabolism, 106(3).

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Targeted Sequencing of Mutated Genes in Multiple Myeloma

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Samples from 53 patients (10 with tetraploidy, 25 with amp(1q) and 18 control MM as determined by FISH) were analyzed by custom hybridization‐based sequencing panel of 28 genes known to be mutated in MM (Table S1). Of these patients, 39 were treatment‐naive and 14 were relapsed/refractory. To be considered, the unsorted samples or the isolated CD138+ plasma cells had to show CAs in at least 40% of the cells as determined by prior FISH analysis. Unsorted samples were prepared from methanol:acetic acid‐fixed cells as previously described.²⁶ Libraries were sequenced on a NextSeq 500 using 150‐bp paired‐end reads (Illumina, San Diego, CA). Using DRAGEN Somatic app (v3.8.4) with default parameters (tumor‐only mode) on BaseSpace (Illumina), reads were mapped to the human reference genome (hg38) and single‐nucleotide variants (SNVs) and indels were called. Sequencing artifacts were flagged using a panel of normals and filtered out. Variant Interpreter (Illumina) was used to annotate passed variants with coding consequences, a variant allele frequency of ≥5% and a frequency of less than 0.05% in the Genome Aggregation Database. The passed variants were visually inspected in the Integrative Genomics Viewer.

Locher M., Jukic E., Vogi V., Keller M.A., Kröll T., Schwendinger S., Oberhuber K., Verdorfer I., Mühlegger B.E., Witsch‐Baumgartner M., Nachbaur D., Willenbacher W., Gunsilius E., Wolf D., Zschocke J, & Steiner N. (2022). Amp(1q) and tetraploidy are commonly acquired chromosomal abnormalities in relapsed multiple myeloma. European Journal of Haematology, 110(3), 296-304.

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Comprehensive Bioinformatic Workflow for Genetic Variant Analysis

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Bioinformatics and data analysis start from checking each run quality through assessing the specifications based on Illumina PhiX control library which support cluster densities between 865-965 k/mm 2 clusters passing filter for v2 chemistry. The second item is the quality score (Q-score) which is a prediction of the probability of an error in base calling. The percentage of bases > Q30 is averaged across the entire run. The quality scores for v2 chemistry > 80% bases higher than Q30 at 2 × 150 bp. The assembly of the reads was run to Genome Reference Consortium Human Build 37 (GRCh37) which is the human reference genome (version hg19). Image processing and Variant Call Format (VCF) file generation were further analyzed, we then annotated these variants using Illumina variant interpreter. Each variant is linked to numerical identifier in Catalogue of Somatic Mutations in Cancer (COSMIC) database. The likely impact of amino acid changes was determined with In Silico Predictions (Sift & PolyPhen) and Functional Analysis through Hidden Markov Models (v2.3) (FATHMM) prediction. The variants were categorized as benign or pathogenic according to ClinVar database. Mutations with low depth, which indicate ≤ 50× depths, mutations with ≤ 5% variant allele frequency, variants quality if < 80% and finally, variant that did not found in COSMIC database were filtered out.

Kassem N., Kassem H., Kassem L, & Hassan M. (2021). Detection of activating mutations in liquid biopsy of Egyptian breast cancer patients using targeted next-generation sequencing: a pilot study. Journal of the Egyptian National Cancer Institute, 33(1).

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